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Evaluation of Association Rules Extracted during Anomaly Explanation

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F15%3A00447917" target="_blank" >RIV/67985807:_____/15:00447917 - isvavai.cz</a>

  • Alternative codes found

    RIV/68407700:21240/15:00232443

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Evaluation of Association Rules Extracted during Anomaly Explanation

  • Original language description

    Discovering anomalies within data is nowadays very important, because it helps to uncover interesting events. Consequently, a considerable amount of anomaly detection algorithms was proposed in the last few years. Only a few papers about anomaly detection at least mentioned why some samples were labelled as anomalous. Therefore, we proposed a method allowing to extract rules explaining the anomaly from an ensemble of specifically trained decision trees, called sapling random forest. Our method is able to interpret the output of an arbitrary anomaly detector. The explanation is given as conjunctions of atomic conditions, which can be viewed as antecedents of association rules. In this work we focus on selection, post processing and evaluation of those rules. The main goal is to present a small number of the most important rules. To achieve this, we use quality measures such as lift and confidence boost. The resulting sets of rules are experimentally and empirically evaluated on two arti

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GA13-17187S" target="_blank" >GA13-17187S: Constructing Advanced Comprehensible Classifiers</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2015

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings ITAT 2015: Information Technologies - Applications and Theory

  • ISBN

    978-1-5151-2065-0

  • ISSN

    1613-0073

  • e-ISSN

  • Number of pages

    7

  • Pages from-to

    143-149

  • Publisher name

    Technical University & CreateSpace Independent Publishing Platform

  • Place of publication

    Aachen & Charleston

  • Event location

    Slovenský Raj

  • Event date

    Sep 17, 2015

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article